Senior Engineer - Artificial Intelligence

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Tucows Domains

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$120K - $145K/yr

Tech Stack

About the Role

Tucows Domains seeks a Senior AI Engineer to develop intelligent agents and AI-driven features for our domain management platform. The role involves designing scalable multi-agent systems and advanced RAG architectures, owning the complete lifecycle of AI services from model selection through Kubernetes deployment, and writing primarily Python code while collaborating on Go infrastructure. The engineer will also establish ethical AI standards including data privacy protocols, bias mitigation, and security practices. The position bridges cutting-edge LLM research and production-grade software engineering, focusing on automating complex tasks with infrastructure-grade reliability.

Responsibilities:

  • Design and develop scalable multi-agent systems and advanced RAG architectures
  • Own the complete lifecycle of AI services from model selection through Kubernetes deployment
  • Write primarily Python code while collaborating on Go infrastructure
  • Establish ethical AI standards: data privacy protocols, bias mitigation, security practices

Required Tech Stack & Skills:

  • Languages: Advanced Python proficiency; Go experience or rapid learning ability strongly preferred
  • Frameworks: Large Language Models (LLMs) and agentic frameworks
  • Infrastructure: Docker, CI/CD pipelines, AWS cloud-based inference
  • 5+ years shipping production applications

Additional Requirements:

  • Strong communication abilities for technical and non-technical audiences
  • Mentoring capability across engineer levels
  • Legal work authorization in Canada/USA for 37.5+ hours weekly

Company Context:

Tucows operates globally as the world's largest wholesale domain registrar managing DNS infrastructure across Ascio, Enom, Hover, and OpenSRS brands, emphasizing remote-first work across 20+ countries.

Location: Remote (US/Canada only).

Salary:

  • US: $120,000-$145,000 USD
  • Canada: $126,090-$140,100 CAD
  • Range may vary based on location and experience.
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